import os
from moviepy import VideoFileClip, TextClip, CompositeVideoClip

import librosa
import nltk
from nltk.sentiment import SentimentIntensityAnalyzer
#视频分割：将整部电影分割成多个短片段，便于后续处理。
def split_video(video_path, segment_length=10):
    clip = VideoFileClip(video_path)
    duration = clip.duration
    segments = []
    for i in range(0, int(duration), segment_length):
        segment = clip.subclipped(i, i + segment_length)
        segment_path = f"segments/segment_{i}.mp4"
        segment.write_videofile(segment_path)
        segments.append(segment_path)
    return segments

#音频提取：从视频片段中提取音频数据，用于情感分析和语音识别。
def extract_audio(video_path):
    clip = VideoFileClip(video_path)
    audio_path = video_path.replace('.mp4', '.wav')
    clip.audio.write_audiofile(audio_path)
    return audio_path

#字幕提取：利用OCR技术提取视频中的字幕，用于文本分析。
def extract_subtitles(video_path):
    # 使用OCR技术提取字幕，此处简化为伪代码
    subtitles = "伪代码：提取字幕"
    return subtitles

#音频特征：提取音频的MFCC、能量等特征，用于情感分析。
def extract_audio_features(audio_path):
       y, sr = librosa.load(audio_path)
       mfccs = librosa.feature.mfcc(y=y, sr=sr)
       return mfccs

#视频特征：提取视频的帧率、颜色直方图等特征，用于视觉分析。
def extract_text_features(subtitles):
       sia = SentimentIntensityAnalyzer()
       sentiment = sia.polarity_scores(subtitles)
       return sentiment


if __name__ == "__main__":
    # filenames=os.listdir("处理前")
    # video =os.path.join("处理前",filenames[0])
    # a=split_video(video)
    # print(a)
    # b=extract_audio(f"segments/segment_0.mp4")
    # print(b)
    c=extract_audio_features(f"segments/segment_0.wav")